Pictorial images are often classified by the particular event, subject or the like for convenience of retrieving, reviewing, and albuming of the images. Typically, this has been achieved by manually segmenting the images, or by the below-described automated method. The automated method includes grouping by color, shape or texture of the images for partitioning the images into groups of similar image characteristics.
Although the presently known and utilized methods for partitioning images are satisfactory, there are drawbacks. The manual classification is obviously time consuming, and the automated process, although theoretically classifying the images into events, is susceptible to miss-classification due to the inherent inaccuracies involved with classification by color, shape or texture.
U.S. Pat. No. 6,606,411 “Method for automatically classifying images into events,” by Loui and Pavie sets forth an arrangement for automatically classifying images into events based on both date-time and image color content information. Although this system is quite effective, it does not take into consideration the fact that certain images of a collection can have incomplete date-time information. Incomplete date-time information includes images and video clips (i.e., content) that either contain the date, the time, a wrong date-time, or none of the above in their header or metadata portion of the content.